479 research outputs found
Synthesizing Switching Controllers for Hybrid Systems by Continuous Invariant Generation
We extend a template-based approach for synthesizing switching controllers
for semi-algebraic hybrid systems, in which all expressions are polynomials.
This is achieved by combining a QE (quantifier elimination)-based method for
generating continuous invariants with a qualitative approach for predefining
templates. Our synthesis method is relatively complete with regard to a given
family of predefined templates. Using qualitative analysis, we discuss
heuristics to reduce the numbers of parameters appearing in the templates. To
avoid too much human interaction in choosing templates as well as the high
computational complexity caused by QE, we further investigate applications of
the SOS (sum-of-squares) relaxation approach and the template polyhedra
approach in continuous invariant generation, which are both well supported by
efficient numerical solvers
When Less Is More: Consequence-Finding in a Weak Theory of Arithmetic
This paper presents a theory of non-linear integer/real arithmetic and
algorithms for reasoning about this theory. The theory can be conceived as an
extension of linear integer/real arithmetic with a weakly-axiomatized
multiplication symbol, which retains many of the desirable algorithmic
properties of linear arithmetic. In particular, we show that the conjunctive
fragment of the theory can be effectively manipulated (analogously to the usual
operations on convex polyhedra, the conjunctive fragment of linear arithmetic).
As a result, we can solve the following consequence-finding problem: given a
ground formula F, find the strongest conjunctive formula that is entailed by F.
As an application of consequence-finding, we give a loop invariant generation
algorithm that is monotone with respect to the theory and (in a sense)
complete. Experiments show that the invariants generated from the consequences
are effective for proving safety properties of programs that require non-linear
reasoning
Automatic modular abstractions for template numerical constraints
We propose a method for automatically generating abstract transformers for
static analysis by abstract interpretation. The method focuses on linear
constraints on programs operating on rational, real or floating-point variables
and containing linear assignments and tests. In addition to loop-free code, the
same method also applies for obtaining least fixed points as functions of the
precondition, which permits the analysis of loops and recursive functions. Our
algorithms are based on new quantifier elimination and symbolic manipulation
techniques. Given the specification of an abstract domain, and a program block,
our method automatically outputs an implementation of the corresponding
abstract transformer. It is thus a form of program transformation. The
motivation of our work is data-flow synchronous programming languages, used for
building control-command embedded systems, but it also applies to imperative
and functional programming
Mori Dream Spaces
This article is based on the 7th Takagi Lectures that the author delivered at the University of Tokyo on November 21-23, 2009.We explore the circle of ideas connecting finite generation of the Cox ring, Mori dream spaces and invariant theory
SecDec-3.0: numerical evaluation of multi-scale integrals beyond one loop
SecDec is a program which can be used for the factorization of dimensionally
regulated poles from parametric integrals, in particular multi-loop integrals,
and the subsequent numerical evaluation of the finite coefficients. Here we
present version 3.0 of the program, which has major improvements compared to
version 2: it is faster, contains new decomposition strategies, an improved
user interface and various other new features which extend the range of
applicability.Comment: 46 pages, version to appear in Comput.Phys.Com
Parametric Polyhedra with at least Lattice Points: Their Semigroup Structure and the k-Frobenius Problem
Given an integral matrix , the well-studied affine semigroup
\mbox{ Sg} (A)=\{ b : Ax=b, \ x \in {\mathbb Z}^n, x \geq 0\} can be
stratified by the number of lattice points inside the parametric polyhedra
. Such families of parametric polyhedra appear in
many areas of combinatorics, convex geometry, algebra and number theory. The
key themes of this paper are: (1) A structure theory that characterizes
precisely the subset \mbox{ Sg}_{\geq k}(A) of all vectors b \in \mbox{
Sg}(A) such that has at least solutions. We
demonstrate that this set is finitely generated, it is a union of translated
copies of a semigroup which can be computed explicitly via Hilbert bases
computations. Related results can be derived for those right-hand-side vectors
for which has exactly solutions or fewer
than solutions. (2) A computational complexity theory. We show that, when
, are fixed natural numbers, one can compute in polynomial time an
encoding of \mbox{ Sg}_{\geq k}(A) as a multivariate generating function,
using a short sum of rational functions. As a consequence, one can identify all
right-hand-side vectors of bounded norm that have at least solutions. (3)
Applications and computation for the -Frobenius numbers. Using Generating
functions we prove that for fixed the -Frobenius number can be
computed in polynomial time. This generalizes a well-known result for by
R. Kannan. Using some adaptation of dynamic programming we show some practical
computations of -Frobenius numbers and their relatives
A Sums-of-Squares Extension of Policy Iterations
In order to address the imprecision often introduced by widening operators in
static analysis, policy iteration based on min-computations amounts to
considering the characterization of reachable value set of a program as an
iterative computation of policies, starting from a post-fixpoint. Computing
each policy and the associated invariant relies on a sequence of numerical
optimizations. While the early research efforts relied on linear programming
(LP) to address linear properties of linear programs, the current state of the
art is still limited to the analysis of linear programs with at most quadratic
invariants, relying on semidefinite programming (SDP) solvers to compute
policies, and LP solvers to refine invariants.
We propose here to extend the class of programs considered through the use of
Sums-of-Squares (SOS) based optimization. Our approach enables the precise
analysis of switched systems with polynomial updates and guards. The analysis
presented has been implemented in Matlab and applied on existing programs
coming from the system control literature, improving both the range of
analyzable systems and the precision of previously handled ones.Comment: 29 pages, 4 figure
- …